Project Grant R42HL106818

This $717,712 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development and evaluation of a knowledge-enhanced and interpretable radiology report generation framework using longitudinal, multimodal electronic health record data and domain knowledge. The awardee, Joan & Sanford I Weill Medical College of Cornell University, will build a...

The National Science Foundation awarded Cardiophi LLC $532,000 under the Technology, Innovation, and Partnerships program to develop an artificial intelligence solution for the automated interpretation of electrocardiograms. The project aims to refine existing deep learning-based algorithms for detecting irregular heartbeats, develop methods for predicting the onset of cardiac arrhythmias, and create interpretable and explainable tools to provide insights from ECG signals to clinicians....

This Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research program (CFDA 93.837), provides $742,395 to Case Western Reserve University (CWRU) to develop and validate a machine learning-based analysis of coronary artery calcium scans (CTCS) to identify biomarkers for predicting heart failure risk. The 4-year project aims to create an automated tool for extracting CTCS-derived radiomics, develop a comprehensive heart failure risk...

This Project Grant from the National Heart, Lung and Blood Institute, part of the Department of Health and Human Services, was awarded under the Cardiovascular Diseases Research program (CFDA 93.837) to develop clinical software to support quantitative analysis and interpretation of myocardial contrast echocardiography (MCE) data. Narnar, LLC received $757,197 to create software modules that enhance MCE's ability to identify coronary microvascular dysfunction (MVD). The software will average...

Federal Grant Award Summary PulseImaging.ai, LLC received a $304,415 Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI) under the Cardiovascular Diseases Research program (CFDA 93.837), effective August 15, 2025, with a completion date of August 14, 2026. The award funds development of artificial intelligence (AI)-based software to predict future cardiovascular events by analyzing CT Calcium Score (CTCS) screening images. The project leverages a collaborative team...

Rnet Technologies Inc. received a $768,283.44 Project Grant award from the National Institutes of Health's National Institute of Biomedical Imaging and Bioengineering on September 30, 2021 to develop techniques enabling next generation machine learning for large scale image analysis through March 29, 2022. Under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286), Rnet will develop software to automatically map deep learning networks...

This $255,807 National Science Foundation project grant will fund the development of an AI-assisted software system to accelerate the labeling of medical tomographic images. Administered through the NSF Directorate for Engineering's Engineering program (CFDA 47.041), the grant aims to extract new information from medical images and improve patient outcomes. Alienbyte Scientific Software Inc. will apply machine learning algorithms to create an adaptive system that evolves to increase the speed,...

This Project Grant award from the National Heart, Lung, and Blood Institute (NHLBI), under the Cardiovascular Diseases Research federal grant program (CFDA 93.837), will support a $704,611 research project to develop and validate an AI-based model, named EchoNext, that can accurately detect undiagnosed structural heart disease (SHD) from electrocardiogram (ECG) data. The project aims to: 1) prospectively validate the accuracy of EchoNext in detecting undiagnosed SHD in patients presenting to...

This Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) provides $800,000 to develop an intelligent radiology platform through human-machine cooperation. The awardee, Georgia Tech Research Corporation, will create an accurate medical image labeling tool using state-of-the-art artificial intelligence algorithms to maximize accuracy and minimize inter- and intra-reader variability among radiologists. The tool will provide...

This three-year, $651,130 National Science Foundation Project Grant will support the development of Pathoradi, an interactive web server for artificial intelligence-assisted radiologic-pathologic image analysis, correlation and visualization at Howard University. The server aims to address current challenges in comparing radiologic and pathologic images through three components: deep learning algorithms for quantifying cell morphological phenotypes in whole brain sections, a graphical and...